CN112859005A - Method for detecting metal straight cylinder structure in multi-channel ground penetrating radar data - Google Patents
Method for detecting metal straight cylinder structure in multi-channel ground penetrating radar data Download PDFInfo
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Abstract
The invention discloses a method for detecting a metal straight cylinder structure in multi-channel ground penetrating radar data, which comprises the following steps: acquiring m multiplied by c radar data bscan in an area to be detected; recording an image corresponding to jth radar data bscan of the ith radar data batch as img _ ij; performing two-dimensional hyperbolic curve detection on any image img _ ij, and obtaining k metal cylindrical structure targets; recording a Set of metal cylindrical structure targets in the image img _ ij as Set _ ij, and performing two-dimensional hyperbolic curve detection on jth radar data bscan of the ith radar data batch to obtain m sets; sequentially traversing any metal cylindrical structure target in the metal cylindrical structure target Set _ ij, and searching a two-dimensional target in an area ratio mode to obtain a three-dimensional metal cylindrical structure target Set _3 d; and synthesizing the three-dimensional metal cylindrical structure target Set in the Set _3d to obtain a metal straight cylindrical structure.
Description
Technical Field
The invention relates to the technical field of radar data processing, in particular to a method for detecting a metal straight cylinder structure in multi-channel ground penetrating radar data.
Background
The position corresponding to the metal cylindrical structure in the ground penetrating radar slice image presents an obvious hyperbolic structure, and whether a steel bar or a pipeline (hollow) is distinguished at the position. On multichannel ground penetrating radar equipment, multichannel shallow layer ground penetrating radar during operation hangs on carrying equipment, advances forward simultaneously by carrying equipment a plurality of passageways, assumes to the radar equipment of m passageway, and m can be more than or equal to 1 any integer, and when m was 1, is single channel ground penetrating radar.
In general, the ground penetrating radar works by performing full coverage detection (as shown in fig. 1) on a region, where each detection is performed by using m channel radar data bscan generated by a single travel, i.e. denoted as 1 group of batchs, generally, in the multi-channel ground penetrating radar detection, the number of the axial scan data ascans contained in all bscans in the same batch is the same, while in the full coverage detection, the number of the ascans contained in the radar data bscans in two different batchs is different, which is shown in fig. 2. The multi-channel ground penetrating radar performs detection back and forth in the area c times to generate c groups of batch data, namely c × m radar data bscan, namely radar data of a cube, as shown in fig. 3, each point represents an actual position, the value of each point is the strength of radar echo, the radar echo represents the condition of an underground target, and the radar echo data of a single bscan is subjected to visualization processing as shown in fig. 4.
At present, in the prior art, analysis of multi-channel shallow ground penetrating radar data is generally performed on each slice, and then slice analysis results are integrated to obtain a real three-dimensional geological target detection result, and a metal cylindrical structure target presents an obvious hyperbolic characteristic in a radar slice, as shown in fig. 5. Currently, the automatic detection of underground targets with metal cylindrical structures mainly focuses on the detection of a single bscan, such as mao xing peng "a fast detection method for hyperbolic targets of ground penetrating radar", which mainly performs visualization processing on ground penetrating radar data (with high probability, bscan data) to perform edge detection, performs visualization processing on radar signals to perform edge processing again, and searches for hyperbolic targets after combination, at this time, there is a cluster of hyperbolic results, it is necessary to combine dielectric constant information with the hyperbolic results, extracts from the cluster of hyperbolic results, hyperbolic fixed points and several hyperbolic curves are reflection images belonging to the same steel bar, and obtains n steel bars and fixed point positions thereof, the method is based on a classical image processing algorithm, extracts hyperbolic information in the bscan radar signals, and obtains a plurality of two-dimensional results, but the hyperbolic targets are not necessarily steel bar targets, a metal nut screw (one bit larger) in the ground penetrating radar scan address will also travel the hyperbolic result on the bscan image.
For another Chinese patent with the patent application number of '202010493228.4' and the name of 'an intelligent concrete reinforcing steel bar positioning method based on ground penetrating radar and deep learning', the situation is almost the same as that of 'a method for quickly detecting hyperbolic targets by ground penetrating radar', ssd which is a method for detecting targets based on deep learning is used, and finally, the positions (vertexes) of the hyperbolic targets are also determined, so that how deep the hyperbolic targets are in the ground is determined.
For example, Hatong, "overview of hyperbolic-oriented ground penetrating radar image recognition technology", which summarizes hyperbolic targets currently detected in a bscan image, includes a deep learning method (e.g., "202010493228.4"), and also includes a method based on image processing (e.g., a method for rapidly detecting hyperbolic targets by a ground penetrating radar), but this method is also based on results of the bscan image and is two-dimensional.
In the actual situation, whether the method of classical image processing or deep learning is used, the target detection is carried out on a single bscan image, and because the radar slice image represents the target through the strength of electromagnetic reflected waves, and the actual situation under the road is very complicated, a plurality of false targets exist, and a very obvious hyperbolic characteristic is presented in the single bscan slice image.
Therefore, a method for detecting a metal straight cylinder structure in multi-channel ground penetrating radar data, which is simple in logic, accurate and reliable, is urgently needed to be provided.
Disclosure of Invention
Aiming at the problems, the invention aims to provide a method for detecting a metal straight cylinder structure in multi-channel ground penetrating radar data, and the technical scheme adopted by the invention is as follows:
a method for detecting a metal straight cylinder structure in multi-channel ground penetrating radar data comprises the following steps:
in an area to be detected, grid-shaped turning back detection is performed for c times along the parallel direction by adopting an m-channel ground penetrating radar, and m multiplied by c radar data bscan be obtained; the m radar data bscan form a radar data batch; the c radar data batch form radar data cscan of the area to be detected; the radar data cscan is equal to m × c radar data bscan; both m and c are integers greater than 1;
preprocessing any radar data bscan and performing visualization processing;
recording an image corresponding to jth radar data bscan of the ith radar data batch as img _ ij; i is more than 0 and less than or equal to c, and j is more than 0 and less than or equal to m;
performing two-dimensional hyperbolic curve detection on any image img _ ij, obtaining k metal cylindrical structure targets, and recording that any metal cylindrical structure Target is Target _ ij _ u, and u is more than 0 and less than or equal to k; the Target _ ij _ u with the metal cylindrical structure contains position information; the position information comprises the center point coordinates, the width and the height of the metal cylindrical structure Target _ ij _ u in the image img _ ij;
recording a Set of metal cylindrical structure targets in the image img _ ij as Set _ ij, and performing two-dimensional hyperbolic curve detection on jth radar data bscan of the ith radar data batch to obtain m × c sets;
sequentially traversing any metal cylindrical structure target in the metal cylindrical structure target Set _ ij from the metal cylindrical structure target Set _ i1, and searching a two-dimensional target in an area ratio mode until any image img _ ij completes searching to obtain a three-dimensional metal cylindrical structure target Set which is Set _3 d;
and synthesizing the three-dimensional metal cylindrical structure target Set in the Set _3d to obtain a metal straight cylindrical structure.
Further, the method sequentially traverses any metal cylindrical structure target in the metal cylindrical structure target Set _ ij from the metal cylindrical structure target Set _ i1, searches for a two-dimensional target in an area ratio manner until any image img _ ij completes the search, and obtains a three-dimensional metal cylindrical structure target Set as Set _3d, and includes the following steps:
sequentially traversing the metal cylindrical structure targets in any metal cylindrical structure target Set _ ij from the metal cylindrical structure target Set _ i1,
marking the Target of the s-1 th metal cylindrical structure Target set as Target _ i (s-1) _ p(s-1)；p(s-1)Is an integer which is more than 1 and less than the total number of targets of the s-1 th metal cylindrical structure target set; the Target _ i (s-1) _ p(s-1)The corresponding position information in the region is Rect _ i (s-1) _ p(s-1)S is more than 0 and less than or equal to j;
marking the Target of the s-th metal cylindrical structure Target set as Target _ is _ ps；psIs an integer which is more than 1 and less than the total number of targets of the s-th metal-like cylindrical structure target set; the Target _ is _ psThe corresponding position information in the region is Rect _ is _ ps；
Obtaining position information Rect _ i (s-1) _ p(s-1)And position information Rect _ is _ psThe area of intersection iSize;
obtaining position information Rect _ i (s-1) _ p(s-1)And position information Rect _ is _ psThe union area uisize;
obtaining the ratio of the intersection area iSize to the union area uSize, and if the ratio is greater than a preset threshold value thresh, determining that the ratio is a two-dimensional target detected by adjacent radar data bscan in the same radar data batch at the same position;
and (4) completing two-dimensional target search until any image img _ ij, and forming a three-dimensional metal cylindrical structure target Set which is Set _3 d.
Further, the synthesizing the three-dimensional metal cylindrical structure target in the Set _3d from the three-dimensional metal cylindrical structure target Set to obtain the metal straight cylindrical structure includes the following steps:
step S31, arbitrarily taking two three-dimensional metal cylindrical structure targets from the three-dimensional metal cylindrical structure target Set _3d, and marking as a three-dimensional metal cylindrical structure target pip3d _ a and a three-dimensional metal cylindrical structure target pip3d _ b;
step S32, if the distance between the end points of the three-dimensional metal cylindrical structure target pip3d _ a and the three-dimensional metal cylindrical structure target pip3d _ b is smaller than a preset threshold minEndDis, fitting a three-dimensional straight line by using the center point coordinates corresponding to any two-dimensional target in the three-dimensional metal cylindrical structure target pip3d _ a and the three-dimensional metal cylindrical structure target pip3d _ b; otherwise, go to step S35;
step S33, if the vertical distance between any two-dimensional target in the three-dimensional metal cylindrical structure target pip3d _ a and the three-dimensional metal cylindrical structure target pip3d _ b and a fitted three-dimensional straight line is smaller than a threshold minDisToline, synthesizing the three-dimensional metal cylindrical structure target pip3d _ a and the three-dimensional metal cylindrical structure target pip3d _ b into a three-dimensional target pip3d _ new, and obtaining a metal straight cylindrical structure by using the three-dimensional target pip3d _ new; otherwise, go to step S35;
step S34, repeating the steps S31 to S33, storing the three-dimensional target pip3d _ new into a data Set, updating to obtain a metal cylindrical structure until the comparison and judgment of the three-dimensional metal cylindrical structure target Set _3d are completed, and deleting the three-dimensional metal cylindrical structure target pip3d _ a and the three-dimensional metal cylindrical structure target pip3d _ b corresponding to the three-dimensional target pip3d _ new which is not synthesized;
and step S35, composing by using the three-dimensional metal cylindrical structure target of the non-synthesized three-dimensional target pip3d _ new to obtain a metal straight cylindrical structure.
Preferably, the three-dimensional straight line is fitted by a least square method.
Preferably, the threshold thresh is 0.5.
Preferably, the threshold minEndDis takes a value of 0.3.
Preferably, the threshold minDisToline is 0.05.
Preferably, any radar data bscan is preprocessed, and the preprocessing comprises zero offset adjustment, zero point adjustment, filtering and gain adjustment.
Preferably, two-dimensional hyperbolic curve detection is performed on any image img _ i using FRCNN.
Compared with the prior art, the invention has the following beneficial effects:
(1) the method skillfully adopts an area ratio mode to search the two-dimensional target, and has the advantages of representing the relevance of the two-dimensional targets detected by adjacent bscans of the same batch;
(2) the method adopts a three-dimensional metal cylindrical structure target to synthesize so as to obtain a metal straight cylindrical structure, in an actual scene, the straight cylindrical structures are very many, and the method synthesizes small-section three-dimensional targets in a straight line fitting mode;
in conclusion, the method has the advantages of simple logic, accuracy, reliability and the like, and has high practical value and popularization value in the technical field of radar data processing.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention, and therefore should not be considered as limiting the scope of protection, and it is obvious for those skilled in the art that other related drawings can be obtained according to these drawings without inventive efforts.
Fig. 1 is a schematic diagram of a ground detection path in the prior art.
Fig. 2 is a diagram of prior art ground detection radar data.
FIG. 3 is a diagram of prior art radar data for a cube.
FIG. 4 is a graph of prior art echo data.
Fig. 5 is a hyperbolic characteristic diagram in the prior art.
FIG. 6 is a diagram of target locations for the present invention.
FIG. 7 is a diagram of the relationship of the location and the area of the present invention.
FIG. 8 is a three-dimensional object set diagram of the present invention.
FIG. 9 is a point-vector fit line graph of the present invention.
Detailed Description
To further clarify the objects, technical solutions and advantages of the present application, the present invention will be further described with reference to the accompanying drawings and examples, and embodiments of the present invention include, but are not limited to, the following examples. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Examples
As shown in fig. 6 to 9, the present embodiment provides a method for detecting a metal-like right cylinder structure in multi-channel ground penetrating radar data, including the following steps:
firstly, in an area to be detected, performing grid-shaped turn-back detection for c times along the parallel direction by using an m-channel ground penetrating radar to obtain mxc radar data bscan; the m radar data bscan form a radar data batch; the c radar data batch form radar data cscan of the area to be detected; the radar data cscan is equal to m × c radar data bscan; both m and c are integers greater than 1; in this embodiment, m is 7.
And secondly, preprocessing (adjusting zero offset, adjusting zero point, filtering and adjusting gain) any radar data bscan, and performing visualization processing.
Thirdly, recording an image corresponding to jth radar data bscan of the ith radar data batch as img _ ij; i is more than 0 and less than or equal to c, and j is more than 0 and less than or equal to m.
And fourthly, detecting the two-dimensional hyperbolic steel bar structure for the image img _ ij, wherein a classical image processing algorithm (such as 'a method for quickly detecting a hyperbolic target of a ground penetrating radar') can be adopted, and a deep learning mode can also be adopted without limitation. In this embodiment, FRCNN is adopted to train a brother type sample picture of an existing radar slice image, and then the trained model is used to identify an image img _ ij, which is a result of the type of a metal cylinder.
Fifthly, k metal cylindrical structure targets are obtained, and any one metal cylindrical structure Target is recorded as Target _ ij _ u, wherein u is more than 0 and is less than or equal to k; the Target _ ij _ u with the metal cylindrical structure contains position information; the position information comprises the center point coordinates, the width and the height of the metal cylindrical structure Target _ ij _ u in the image img _ ij. When the ground penetrating radar works, each Ascan not only has data, but also has a corresponding Position, as shown in fig. 1, so that the target has a real coordinate Position in addition to an image Position, the Position of the center point of the target in this embodiment represents the actual Position of the target, and the Position includes x, y, latitude, longtude, height. Wherein x and y are positions in a coordinate system used in the detection task, and latitude, longtude and height are longitude and latitude heights of the point in the terrestrial coordinate system.
And sixthly, recording that the Set of the metal cylindrical structure targets in the image img _ ij is Set _ ij, and performing two-dimensional hyperbolic curve detection on the jth radar data bscan of the ith radar data batch to obtain m × c sets, Set _ i1, Set _ i2, … … and Set _ im.
Step seven, sequentially traversing any metal cylindrical structure target in the metal cylindrical structure target Set _ ij from the metal cylindrical structure target Set _ i1, and searching a two-dimensional target in an area ratio mode until any image img _ ij finishes searching to obtain a three-dimensional metal cylindrical structure target Set which is Set _3 d; specifically, the method comprises the following steps:
(11) sequentially traversing the metal cylindrical structure targets in any metal cylindrical structure target Set _ ij from the metal cylindrical structure target Set _ i1,
(12) marking the Target of the s-1 th metal cylindrical structure Target set as Target _ i (s-1) _ p(s-1)； p(s-1)Is a target set which is larger than 1 and smaller than the s-1 th metal cylinder structure target setA nominal total number of integers; the Target _ i (s-1) _ p(s-1)The corresponding position information in the region is Rect _ i (s-1) _ p(s-1)S is more than 0 and less than or equal to j;
(13) marking the Target of the s-th metal cylindrical structure Target set as Target _ is _ ps；psIs an integer which is more than 1 and less than the total number of targets of the s-th metal-like cylindrical structure target set; the Target _ is _sThe corresponding position information of p in the region is Rect _ is _ ps；
(14) Obtaining position information Rect _ i (s-1) _ p(s-1)And position information Rect _ is _ psThe area of intersection iSize;
(15) obtaining position information Rect _ i (s-1) _ p(s-1)And position information Rect _ is _ psThe union area uisize;
(16) and (5) obtaining the ratio of the intersection area iSize to the union area uSize, and if the ratio is greater than a preset threshold thresh, taking the value as 0.5. Then the two-dimensional target is detected at the same position by the adjacent radar data bscan in the same radar data batch; until a two-dimensional detection result meeting the condition cannot be found in the next adjacent bscan picture, or until the searching of all the bscan pictures of the current batch is completed, so that the searching of 1 three-dimensional target in the batch is completed, the three-dimensional target is marked as pip3d, and the two-dimensional target contained in the pip3d is deleted from the corresponding set;
(17) repeating the steps (11) to (16), and performing two-dimensional target search on all two-dimensional results of img _ i1, img _ i2 and …; and repeatedly obtaining two-dimensional target search within the range of i being more than 0 and less than or equal to c, and forming a target Set of the three-dimensional metal cylindrical structure into Set _3 d.
And step eight, synthesizing the three-dimensional metal cylindrical structure target in the Set _3d from the three-dimensional metal cylindrical structure target Set to obtain a metal straight cylindrical structure. In this embodiment, a single three-dimensional target includes a set of physically adjacent two-dimensional targets, each two-dimensional target has a central point, as shown in fig. 3, the positions of bscan two-dimensional targets of different batchs at their bscan not be synthesized into a three-dimensional target in a corresponding manner similar to bscan img in the batch, and only the real positions of the three dimensions can be used, specifically:
step S31, arbitrarily taking two three-dimensional metal cylindrical structure targets from the three-dimensional metal cylindrical structure target Set _3d, and marking as a three-dimensional metal cylindrical structure target pip3d _ a and a three-dimensional metal cylindrical structure target pip3d _ b;
step S32, if the distance between the end points of the three-dimensional metal cylindrical structure target pip3d _ a and the three-dimensional metal cylindrical structure target pip3d _ b is smaller than a preset threshold minEndDis, and the value of the distance is 0.3, a three-dimensional straight line is fit by using the coordinates of the center points corresponding to any two-dimensional target in the three-dimensional metal cylindrical structure target pip3d _ a and the three-dimensional metal cylindrical structure target pip3d _ b (that is, the center points of all two-dimensional targets included in the two three-dimensional targets participate in fitting the straight line), where the method for fitting the three-dimensional straight line in this embodiment is an existing known method; otherwise, go to step S35;
in this step, a spatial straight line is expressed by a point-vector equation, a three-dimensional straight line is fitted by a least square method, and as shown in fig. 9, a straight line is expressed by using a unit vector D of a point P and a point P in the direction of the straight line, and an arbitrary point P is expressed by using a unit vector D of the point P and the point P in the direction of the straight lineiThe vector to P is marked as V, then any point PiThe distance to the straight line is denoted V2-(V.D)2The symbol ". multidot." denotes a dot product between vectors. And constructing a loss function during straight line fitting, wherein the expression is as follows:
wherein N represents the number of points;
this embodiment optimizes the loss function using a gradient descent method to obtain an equation fitting a straight line.
In step S33, if the vertical distance between any two-dimensional target in the three-dimensional metal cylindrical structure target pip3d _ a and the three-dimensional metal cylindrical structure target pip3d _ b and the fitted three-dimensional straight line is smaller than the threshold minDisToline, the value is 0.05. Synthesizing the three-dimensional metal cylindrical structure target pip3d _ a and the three-dimensional metal cylindrical structure target pip3d _ b into a three-dimensional target pip3d _ new, and obtaining a metal straight cylindrical structure by using the three-dimensional target pip3d _ new; otherwise, go to step S35;
step S34, repeating the steps S31 to S33, storing the three-dimensional target pip3d _ new into a data Set, updating to obtain a metal cylindrical structure until the comparison and judgment of the three-dimensional metal cylindrical structure target Set _3d are completed, and deleting the three-dimensional metal cylindrical structure target pip3d _ a and the three-dimensional metal cylindrical structure target pip3d _ b corresponding to the three-dimensional target pip3d _ new which is not synthesized; in the present embodiment, the two-dimensional targets in the three-dimensional targets pip3d _ new are arranged by the three-dimensional metal cylindrical structure target pip3d _ a and the two-dimensional targets in the three-dimensional metal cylindrical structure target pip3d _ b in the order of their fitting straight lines. In this embodiment, after deleting the three-dimensional metal cylindrical structure target pip3d _ a and the three-dimensional metal cylindrical structure target pip3d _ b, the three-dimensional target pip3d _ new is placed in the set, the whole process is detection without stopping, if two or more three-dimensional targets pip3d _ new can synthesize a larger three-dimensional target, the three-dimensional target pip3d _ new corresponding to the synthesized larger three-dimensional target is deleted, and finally, any two remaining targets in the set cannot be synthesized, so that the set is the detected final result.
Step S35, obtaining another metal straight cylindrical structure by using the three-dimensional metal cylindrical structure target composition of the non-synthesized three-dimensional target pip3d _ new, in this embodiment, the three-dimensional target pip3d _ new may form a metal straight cylindrical structure; in addition, the three-dimensional metal-based cylindrical structure target of the three-dimensional target pip3d _ new may also constitute another metal-based straight cylindrical structure.
The above-mentioned embodiments are only preferred embodiments of the present invention, and do not limit the scope of the present invention, but all the modifications made by the principles of the present invention and the non-inventive efforts based on the above-mentioned embodiments shall fall within the scope of the present invention.
Claims (9)
1. A method for detecting a metal straight cylinder structure in multi-channel ground penetrating radar data is characterized by comprising the following steps:
in an area to be detected, grid-shaped turning back detection is performed for c times along the parallel direction by adopting an m-channel ground penetrating radar, and m multiplied by c radar data bscan be obtained; the m radar data bscan form a radar data batch; the c radar data batch form radar data cscan of the area to be detected; the radar data cscan is equal to m × c radar data bscan; both m and c are integers greater than 1;
preprocessing any radar data bscan and performing visualization processing;
recording an image corresponding to jth radar data bscan of the ith radar data batch as img _ ij; i is more than 0 and less than or equal to c, and j is more than 0 and less than or equal to m;
performing two-dimensional hyperbolic curve detection on any image img _ ij, obtaining k metal cylindrical structure targets, and recording that any metal cylindrical structure Target is Target _ ij _ u, and u is more than 0 and less than or equal to k; the Target _ ij _ u with the metal cylindrical structure contains position information; the position information comprises the center point coordinates, the width and the height of the metal cylindrical structure Target _ ij _ u in the image img _ ij;
recording a Set of metal cylindrical structure targets in the image img _ ij as Set _ ij, and performing two-dimensional hyperbolic curve detection on jth radar data bscan of the ith radar data batch to obtain m × c sets;
sequentially traversing any metal cylindrical structure target in the metal cylindrical structure target Set _ ij from the metal cylindrical structure target Set _ i1, and searching a two-dimensional target in an area ratio mode until any image img _ ij completes searching to obtain a three-dimensional metal cylindrical structure target Set which is Set _3 d;
and synthesizing the three-dimensional metal cylindrical structure target Set in the Set _3d to obtain a metal straight cylindrical structure.
2. The method for detecting the metal-like straight cylinder structure in the multi-channel ground penetrating radar data as claimed in claim 1, wherein the following steps are included, starting from a metal-like cylinder structure target Set _ i1, sequentially traversing any metal-like cylinder structure target in a metal-like cylinder structure target Set _ ij, and searching for a two-dimensional target in an area ratio manner until a search is completed for any image img _ ij, so as to obtain a three-dimensional metal-like cylinder structure target Set _3 d:
sequentially traversing the metal cylindrical structure targets in any metal cylindrical structure target Set _ ij from the metal cylindrical structure target Set _ i1,
marking the Target of the s-1 th metal cylindrical structure Target set as Target _ i (s-1) _ p(s-1)；p(s-1)Is an integer which is more than 1 and less than the total number of targets of the s-1 th metal cylindrical structure target set; the Target _ i (s-1) _ p(s-1)The corresponding position information in the region is Rect _ i (s-1) _ p(s-1)S is more than 0 and less than or equal to j;
marking the Target of the s-th metal cylindrical structure Target set as Target _ is _ ps；psIs an integer which is more than 1 and less than the total number of targets of the s-th metal-like cylindrical structure target set; the Target _ is _ psThe corresponding position information in the region is Rect _ is _ ps；
Obtaining position information Rect _ i (s-1) _ p(s-1)And position information Rect _ is _ psThe area of intersection iSize;
obtaining position information Rect _ i (s-1) _ p(s-1)And position information Rect _ is _ psThe union area uisize;
obtaining the ratio of the intersection area iSize to the union area uSize, and if the ratio is greater than a preset threshold value thresh, determining that the ratio is a two-dimensional target detected by adjacent radar data bscan in the same radar data batch at the same position;
and (4) completing two-dimensional target search until any image img _ ij, and forming a three-dimensional metal cylindrical structure target Set which is Set _3 d.
3. The method for detecting the metal-based straight cylinder structure in the multi-channel ground penetrating radar data as claimed in claim 2, wherein the step of synthesizing the three-dimensional metal-based cylinder structure target in the Set _3d to obtain the metal-based straight cylinder structure comprises the following steps:
step S31, arbitrarily taking two three-dimensional metal cylindrical structure targets from the three-dimensional metal cylindrical structure target Set _3d, and marking as a three-dimensional metal cylindrical structure target pip3d _ a and a three-dimensional metal cylindrical structure target pip3d _ b;
step S32, if the distance between the end points of the three-dimensional metal cylindrical structure target pip3d _ a and the three-dimensional metal cylindrical structure target pip3d _ b is smaller than a preset threshold minEndDis, fitting a three-dimensional straight line by using the center point coordinates corresponding to any two-dimensional target in the three-dimensional metal cylindrical structure target pip3d _ a and the three-dimensional metal cylindrical structure target pip3d _ b; otherwise, go to step S35;
step S33, if the vertical distance between any two-dimensional target in the three-dimensional metal cylindrical structure target pip3d _ a and the three-dimensional metal cylindrical structure target pip3d _ b and a fitted three-dimensional straight line is smaller than a threshold minDisToline, synthesizing the three-dimensional metal cylindrical structure target pip3d _ a and the three-dimensional metal cylindrical structure target pip3d _ b into a three-dimensional target pip3d _ new, and obtaining a metal straight cylindrical structure by using the three-dimensional target pip3d _ new; otherwise, go to step S35;
step S34, repeating the steps S31 to S33, storing the three-dimensional target pip3d _ new into a data Set, updating to obtain a metal cylindrical structure until the comparison and judgment of the three-dimensional metal cylindrical structure target Set _3d are completed, and deleting the three-dimensional metal cylindrical structure target pip3d _ a and the three-dimensional metal cylindrical structure target pip3d _ b corresponding to the three-dimensional target pip3d _ new which is not synthesized;
and step S35, composing by using the three-dimensional metal cylindrical structure target of the non-synthesized three-dimensional target pip3d _ new to obtain a metal straight cylindrical structure.
4. The method for detecting the metal-like right cylindrical structure in the multi-channel ground penetrating radar data as claimed in claim 3, wherein the three-dimensional straight line is fitted by a least square method.
5. The method of claim 2, wherein the threshold thresh is 0.5.
6. The method according to claim 3, wherein the threshold minEndDis is 0.3.
7. The method of claim 3, wherein the threshold minDisToline is 0.05.
8. The method for detecting the metal-like right cylinder structure in the multi-channel ground penetrating radar data as recited in claim 1, wherein any radar data bscan is preprocessed, and the preprocessing comprises zero offset adjustment, zero point adjustment, filtering and gain adjustment.
9. The method for detecting the metal-like straight cylinder structure in the multi-channel ground penetrating radar data as claimed in claim 1, wherein two-dimensional hyperbolic curve detection is performed on any image img _ i by using FRCNN.
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Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1450304A1 (en) * | 2003-02-21 | 2004-08-25 | City University of Hong Kong | Image processing apparatus and method |
| CN106291494A (en) * | 2016-07-21 | 2017-01-04 | 深圳大学 | The SAR cheating interference target identification method and system strengthened based on differential characteristics |
| CN106446919A (en) * | 2016-11-04 | 2017-02-22 | 深圳市航天华拓科技有限公司 | Quick detection method for ground penetrating radar hyperbolic curve target |
| CN107346023A (en) * | 2017-07-04 | 2017-11-14 | 山东工商学院 | A kind of GPR hyperbolic ripple conspicuousness mapping method based on moment characteristics |
| CN107621626A (en) * | 2017-10-09 | 2018-01-23 | 中国矿业大学(北京) | Radar signal Railway Roadbed detection method based on depth convolutional neural networks |
| US20180100944A1 (en) * | 2016-10-11 | 2018-04-12 | Vallon Gmbh | Method for determining a relative dielectric constant and detection method for ground embedded objects |
| CN108037490A (en) * | 2017-11-30 | 2018-05-15 | 中煤航测遥感集团有限公司 | Ground Penetrating Radar Linear Positioning Accuracy Measurement Methods and system |
| CN108153306A (en) * | 2017-12-19 | 2018-06-12 | 成都圭目机器人有限公司 | A kind of autonomous road lossless detection method of robot system |
| CN108665530A (en) * | 2018-04-25 | 2018-10-16 | 厦门大学 | Three-dimensional modeling implementation method based on single picture |
| CN108960183A (en) * | 2018-07-19 | 2018-12-07 | 北京航空航天大学 | A kind of bend target identification system and method based on Multi-sensor Fusion |
| CN110472572A (en) * | 2019-08-14 | 2019-11-19 | 西北工业大学 | The quick identification and classification method of naval target under a kind of complex environment |
| CN110689761A (en) * | 2019-12-11 | 2020-01-14 | 上海赫千电子科技有限公司 | Automatic parking method |
| CN111290396A (en) * | 2020-03-12 | 2020-06-16 | 上海圭目机器人有限公司 | Automatic control method for unmanned ship for pipeline detection |
| WO2020146983A1 (en) * | 2019-01-14 | 2020-07-23 | 深圳市大疆创新科技有限公司 | Lane detection method and apparatus, lane detection device, and mobile platform |
| CN111551927A (en) * | 2020-05-19 | 2020-08-18 | 上海圭目机器人有限公司 | Underground pipeline diameter measuring method based on three-dimensional ground penetrating radar |
| CN111932617A (en) * | 2020-07-15 | 2020-11-13 | 中国科学院上海微系统与信息技术研究所 | Method and system for realizing real-time detection and positioning of regular object |
| GB202017625D0 (en) * | 2019-11-14 | 2020-12-23 | Motional Ad Llc | Sequential fusion for 3D object detection |
-
2021
- 2021-01-11 CN CN202110032018.XA patent/CN112859005B/en active Active
Patent Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1450304A1 (en) * | 2003-02-21 | 2004-08-25 | City University of Hong Kong | Image processing apparatus and method |
| CN106291494A (en) * | 2016-07-21 | 2017-01-04 | 深圳大学 | The SAR cheating interference target identification method and system strengthened based on differential characteristics |
| US20180100944A1 (en) * | 2016-10-11 | 2018-04-12 | Vallon Gmbh | Method for determining a relative dielectric constant and detection method for ground embedded objects |
| CN106446919A (en) * | 2016-11-04 | 2017-02-22 | 深圳市航天华拓科技有限公司 | Quick detection method for ground penetrating radar hyperbolic curve target |
| CN107346023A (en) * | 2017-07-04 | 2017-11-14 | 山东工商学院 | A kind of GPR hyperbolic ripple conspicuousness mapping method based on moment characteristics |
| CN107621626A (en) * | 2017-10-09 | 2018-01-23 | 中国矿业大学(北京) | Radar signal Railway Roadbed detection method based on depth convolutional neural networks |
| CN108037490A (en) * | 2017-11-30 | 2018-05-15 | 中煤航测遥感集团有限公司 | Ground Penetrating Radar Linear Positioning Accuracy Measurement Methods and system |
| CN108153306A (en) * | 2017-12-19 | 2018-06-12 | 成都圭目机器人有限公司 | A kind of autonomous road lossless detection method of robot system |
| CN108665530A (en) * | 2018-04-25 | 2018-10-16 | 厦门大学 | Three-dimensional modeling implementation method based on single picture |
| CN108960183A (en) * | 2018-07-19 | 2018-12-07 | 北京航空航天大学 | A kind of bend target identification system and method based on Multi-sensor Fusion |
| WO2020146983A1 (en) * | 2019-01-14 | 2020-07-23 | 深圳市大疆创新科技有限公司 | Lane detection method and apparatus, lane detection device, and mobile platform |
| CN110472572A (en) * | 2019-08-14 | 2019-11-19 | 西北工业大学 | The quick identification and classification method of naval target under a kind of complex environment |
| GB202017625D0 (en) * | 2019-11-14 | 2020-12-23 | Motional Ad Llc | Sequential fusion for 3D object detection |
| CN110689761A (en) * | 2019-12-11 | 2020-01-14 | 上海赫千电子科技有限公司 | Automatic parking method |
| CN111290396A (en) * | 2020-03-12 | 2020-06-16 | 上海圭目机器人有限公司 | Automatic control method for unmanned ship for pipeline detection |
| CN111551927A (en) * | 2020-05-19 | 2020-08-18 | 上海圭目机器人有限公司 | Underground pipeline diameter measuring method based on three-dimensional ground penetrating radar |
| CN111932617A (en) * | 2020-07-15 | 2020-11-13 | 中国科学院上海微系统与信息技术研究所 | Method and system for realizing real-time detection and positioning of regular object |
Non-Patent Citations (6)
| Title |
|---|
| 卢丹丹: "城市地下管线三维建模关键技术研究", 《测绘通报》, no. 5, pages 117 - 119 * |
| 杜坤升: "城市地下管线探测关键技术研究", 《中国优秀硕士学位论文全文库》, no. 1, pages 038 - 1132 * |
| 王海宁: "三维探地雷达在道路地下病害体探测中的应用", 《中国煤炭地质》, vol. 30, no. 8, pages 70 - 74 * |
| 秦存昌: "隧道病害的探地雷达图像检测方法研究", 《中国优秀硕士学位论文全文数据库》, no. 1, pages 136 - 681 * |
| 胡浩帮等: "基于Faster_R-CNN算法的探地雷达管线目标智能识别", 《城市勘测》, no. 3, pages 203 - 208 * |
| 郝彤: "面向双曲线形态的探地雷达图像识别技术综述", 《电子学报》, vol. 47, no. 6, pages 1369 - 1373 * |
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